Note: you need the value of the Jupyter Token to login to the environment.

The Notebook opens in a new browser window. You can create a new notebook or open a local one. Check out the local folder work for several sample notebooks. For example: open and run pythonForDataAnalysis.ipynb in the work folder. Or open and run Example_word_clouds.ipynb. Or open folder learn-pandas/lessons and start with Python_101.ipynb or Cookbook - Select.ipynb.

The folder work/Data-Analysis contains many notebooks created by Will Koehrsen, who writes many great articles about Data Science and uses Jupyter Notebooks frequently (see his GitHub Repo: https://github.com/WillKoehrsen/Data-Analysis ).

Interactive Widgets

A nice advanced feature in Jupyter Notebooks are the interactive widgets. To have a quick tour of what these widgets can add to a notebook, open work\widgets\Widgets-Overview.ipynb.
The code cell under the Data heading contains an erroneous file reference - or it did when I last checked. Change the contents of the cell to:

Help

Katacoda offerings an Interactive Learning Environment for Developers. This course uses a command line and a pre-configured sandboxed environment for you to use. Below are useful commands when working with the environment.

cd <directory>

Change directory

ls

List directory

echo 'contents' > <file>

Write contents to a file

cat <file>

Output contents of file

Vim

In the case of certain exercises you will be required to edit files or text. The best approach is with Vim. Vim has two different modes, one for entering commands (Command Mode) and the other for entering text (Insert Mode). You need to switch between these two modes based on what you want to do. The basic commands are: